Comparisons of homogeneously reprocessed GPS and VLBI long time-series of troposphere zenith delays and gradients

Troposphere parameters estimated from space-geodetic techniques, like the Global Positioning System (GPS) or Very Long Baseline Interferometry (VLBI), can be used to monitor the atmospheric water vapor content. Although the troposphere can only be monitored at discrete locations, the distribution of the instruments, at least the GPS antennas, can be assumed to be quasi-global. Critical in the data analysis are systematic effects within each single technique that significantly degrade the accuracy and especially the long-term stability of the zenith delay determination. In this paper, consistent time-series of troposphere zenith delays and gradients from homogeneously reprocessed GPS and VLBI solutions are compared for a time period of 11 years. The homogeneity of these completely reprocessed time-series is essential to avoid misinterpretations due to individual model changes. Co-located sites are used to investigate systematic effects and the long-term behavior of the two space-geodetic techniques. Both techniques show common signals in the troposphere parameters at a very high level of precision. The biases between the troposphere zenith delays are at the level of a few millimeters. On the other hand, long-term trends significantly differ for the two techniques, preventing climatological interpretations at present. Tests assume these differences to be due to mathematical artifacts such as different sampling rates and unmodeled semi-annual signals with varying amplitudes.

[1]  M. Rothacher.  Estimation of Station Heights with GPS , 2002 .

[2]  P. Steigenberger,et al.  Absolute phase center corrections of satellite and receiver antennas , 2005 .

[3]  Harald Schuh,et al.  Tropospheric Zenith Delays Determined by VLBI as a Contribution to Climatological Studies , 2004 .

[4]  M. Rothacher,et al.  Estimation of elevation-dependent satellite antenna phase center variations of GPS satellites , 2003 .

[5]  Johannes Boehm,et al.  OCCAM v.6.0 Software for VLBI Data Analysis , 2004 .

[6]  Thomas A. Herring,et al.  Effects of atmospheric azimuthal asymmetry on the analysis of space geodetic data , 1997 .

[7]  Markus Rothacher,et al.  Observation of the Earth system from space , 2006 .

[8]  Peter Steigenberger,et al.  Generation of a consistent absolute phase-center correction model for GPS receiver and satellite antennas , 2007 .

[9]  R. Haas,et al.  Multi-technique comparison of tropospheric zenith delays derived during the CONT02 campaign , 2006 .

[10]  Peter Steigenberger,et al.  CONT02 Analysis and Combination of Long EOP Series , 2006 .

[11]  Detlef Angermann,et al.  ITRS Combination Centre at DGFI - A terrestrial reference frame realization 2003 , 2004 .

[12]  Jan M. Johansson,et al.  Assessing Long Term Trends in the Atmospheric Water Vapor Content by Combining Data From VLBI, GPS, Radiosondes and Microwave Radiometry , 2003 .

[13]  Richard B. Langley,et al.  Comparison of Measurements of Atmospheric Wet Delay by Radiosonde, Water Vapor Radiometer, GPS, and VLBI , 2001 .

[14]  V Tesmer,et al.  An advanced stochastic model for VLBI observations and its application to VLBI data analysis , 2004 .

[15]  Karen D. Baver,et al.  International VLBI Service for Geodesy and Astrometry: 2000 General Meeting Proceedings , 2000 .

[16]  L. Mervart,et al.  Bernese GPS Software Version 5.0 , 2007 .

[17]  Y. Bock,et al.  Anatomy of apparent seasonal variations from GPS‐derived site position time series , 2001 .

[18]  R. Haas,et al.  An inter-comparison study to estimate zenith wet delays using VLBI, GPS, and NWP models , 2000 .

[19]  Markus Rothacher,et al.  CONT02 campaign - combination of VLBI and GPS , 2004 .

[20]  Jan M. Johansson,et al.  Wet path delay and delay gradients inferred from microwave radiometer, GPS and VLBI observations , 2000 .

[21]  U. Hugentobler,et al.  Tropospheric Gradient Estimation at CODE: Results from Global Solutions , 2004 .

[22]  Peter Steigenberger,et al.  Reprocessing of a global GPS network , 2006 .

[23]  Comparison of tropospheric gradients determined by VLBI and GPS , 2001 .

[24]  Volker Tesmer,et al.  Simultaneous Estimation of a TRF, the EOP and a CRF , 2004 .

[25]  Axel Nothnagel,et al.  IVS and its important role in the maintenance of the global reference systems , 2002 .

[26]  J. Saastamoinen,et al.  Contributions to the theory of atmospheric refraction , 1972 .

[27]  R. Pacione,et al.  Comparison of atmospheric parameters derived from GPS, VLBI and a ground-based microwave radiometer in Italy , 2002 .

[28]  Daniel S. MacMillan,et al.  CORE Operation Center Report , 2004 .

[29]  Zuheir Altamimi,et al.  ITRF2000: A new release of the International Terrestrial Reference Frame for earth science applications , 2002 .

[30]  Z. Altamimi,et al.  Results and analysis of the ITRF96. , 1998 .

[31]  A. Niell.  Global mapping functions for the atmosphere delay at radio wavelengths , 1996 .

[32]  D. S. MacMillan,et al.  Atmospheric gradients from very long baseline interferometry observations , 1995 .

[33]  Gunnar Elgered,et al.  Climate monitoring using GPS , 2002 .

[34]  Martin Schmitz,et al.  Results of Absolute Field Calibration of GPS Antenna PCV , 1998 .

[35]  Markus Rothacher,et al.  The International GPS Service (IGS): An interdisciplinary service in support of Earth sciences , 1999 .